Senior DevOps Engineer

The role asks for someone who can run and improve the plumbing behind fast moving software products: build and fix deployment pipelines, run containerized apps on Kubernetes, manage cloud infrastructure with code, and set up monitoring and alerts. A strong candidate brings five to seven years of hands on DevOps or platform work, solid Python and a software engineering background, and the judgment to fix common problems alone while knowing when to bring in others. Reliability, automation and clear documentation matter more than flashy tool lists.

How it fits the AI era

The company sells AI driven customer experience software, so the infrastructure here carries AI workloads and fast release cycles. Much of the routine work, such as pipeline upkeep, alert triage and script writing, can be partly automated, which shifts the human focus toward design, root cause thinking and keeping systems trustworthy. The posting also points to AI deployment and GPU usage as useful extras, so the role sits close to where AI products actually run.

How it builds AI experience

A person in this role would learn how AI products are deployed and kept stable, including pipeline work for AI services and possibly GPU capacity and model operations. That experience is built by taking ownership of onboarding services onto Kubernetes with monitoring and health checks, and by getting involved in AI deployment and MLOps tasks as they come up. The posting treats these as nice to have, so the main path is strong DevOps fundamentals applied to an AI native platform.

Worth showing

• Terraform infrastructure as code
• Python scripting
• Grafana monitoring and alerts

This is our own read, written from the employer's posting and the company's Spotlight. The employer's posting is the source of truth for the role.

About Lucidya

Lucidya provides an artificial intelligence customer experience platform unifying social listening, omnichannel engagement, and autonomous support, per the company.